* [ML][Inference] add tags url param to GET (#51330)
Adds a new URL parameter, `tags` to the GET _ml/inference/<model_id> endpoint.
This parameter allows the list of models to be further reduced to those who contain all the provided tags.
This change adds a new `kibana_admin` role, and deprecates
the old `kibana_user` and`kibana_dashboard_only_user`roles.
The deprecation is implemented via a new reserved metadata
attribute, which can be consumed from the API and also triggers
deprecation logging when used (by a user authenticating to
Elasticsearch).
Some docs have been updated to avoid references to these
deprecated roles.
Backport of: #46456
Co-authored-by: Larry Gregory <lgregorydev@gmail.com>
* [ML][Inference] Adding classification_weights to ensemble models
classification_weights are a way to allow models to
prefer specific classification results over others
this might be advantageous if classification value
probabilities are a known quantity and can improve
model error rates.
Adds a new parameter to regression and classification that enables computation
of importance for the top most important features. The computation of the importance
is based on SHAP (SHapley Additive exPlanations) method.
Backport of #50914
This commit improves the performance of warning value extraction in the
low-level REST client, and is similar to the approach taken in
#24114. There are some differences since the low-level REST client might
be connected to Elasticsearch through a proxy that injects its own
warnings.
* [ML][Inference] PUT API (#50852)
This adds the `PUT` API for creating trained models that support our format.
This includes
* HLRC change for the API
* API creation
* Validations of model format and call
* fixing backport
Since 6.0, the 'template' field has been deprecated in put template requests in
favour of index_patterns. Previously, the PutIndexTemplateRequest would accept
the 'template' field in its 'source' methods and silently convert it to
'index_patterns'. This meant that users specifying 'template' in the source
would not receive a deprecation warning from the server.
This PR makes a small change to no longer silently convert 'template' to
'index_patterns', which ensures that users receive a deprecation warning.
Follow-up to #49460.
Replaces the "funny"
`Function<String, ConstructingObjectParser<T, Void>>` with a much
simpler `ConstructingObjectParser<T, String>`. This makes pretty much
all of our object parsers static.
This adds the necessary named XContent classes to the HLRC for the lang ident model. This is so the HLRC can call `GET _ml/inference/lang_ident_model_1?include_definition=true` without XContent parsing errors.
The constructors are package private as since this classes are used exclusively within the pre-packaged model (and require the specific weights, etc. to be of any use).
If a pipeline referenced by a transform does not exist, we should not allow the transform to be created.
We do allow the pipeline existence check to be skipped with defer_validations, but if the pipeline still does not exist on `_start`, the pipeline will fail to start.
relates: #50135
This PR adds per-field metadata that can be set in the mappings and is later
returned by the field capabilities API. This metadata is completely opaque to
Elasticsearch but may be used by tools that index data in Elasticsearch to
communicate metadata about fields with tools that then search this data. A
typical example that has been requested in the past is the ability to attach
a unit to a numeric field.
In order to not bloat the cluster state, Elasticsearch requires that this
metadata be small:
- keys can't be longer than 20 chars,
- values can only be numbers or strings of no more than 50 chars - no inner
arrays or objects,
- the metadata can't have more than 5 keys in total.
Given that metadata is opaque to Elasticsearch, field capabilities don't try to
do anything smart when merging metadata about multiple indices, the union of
all field metadatas is returned.
Here is how the meta might look like in mappings:
```json
{
"properties": {
"latency": {
"type": "long",
"meta": {
"unit": "ms"
}
}
}
}
```
And then in the field capabilities response:
```json
{
"latency": {
"long": {
"searchable": true,
"aggreggatable": true,
"meta": {
"unit": [ "ms" ]
}
}
}
}
```
When there are no conflicts, values are arrays of size 1, but when there are
conflicts, Elasticsearch includes all unique values in this array, without
giving ways to know which index has which metadata value:
```json
{
"latency": {
"long": {
"searchable": true,
"aggreggatable": true,
"meta": {
"unit": [ "ms", "ns" ]
}
}
}
}
```
Closes#33267
We have about 800 `ObjectParsers` in Elasticsearch, about 700 of which
are final. This is *probably* the right way to declare them because in
practice we never mutate them after they are built. And we certainly
don't change the static reference. Anyway, this adds `final` to these
parsers.
I found the non-final parsers with this:
```
diff \
<(find . -type f -name '*.java' -exec grep -iHe 'static.*PARSER\s*=' {} \+ | sort) \
<(find . -type f -name '*.java' -exec grep -iHe 'static.*final.*PARSER\s*=' {} \+ | sort) \
2>&1 | grep '^<'
```
Adds a `force` parameter to the delete data frame analytics
request. When `force` is `true`, the action force-stops the
jobs and then proceeds to the deletion. This can be used in
order to delete a non-stopped job with a single request.
Closes#48124
Backport of #50553
We have about 800 `ObjectParsers` in Elasticsearch, about 700 of which
are final. This is *probably* the right way to declare them because in
practice we never mutate them after they are built. And we certainly
don't change the static reference. Anyway, this adds `final` to a bunch
of these parsers, mostly the ones in xpack and their "paired" parsers in
the high level rest client. I picked these just to have somewhere to
break the up the change so it wouldn't be huge.
I found the non-final parsers with this:
```
diff \
<(find . -type f -name '*.java' -exec grep -iHe 'static.*PARSER\s*=' {} \+ | sort) \
<(find . -type f -name '*.java' -exec grep -iHe 'static.*final.*PARSER\s*=' {} \+ | sort) \
2>&1 | grep '^<'
```
The additional change to the original PR (#49657), is that `org.elasticsearch.client.cluster.RemoteConnectionInfo` now parses the initial_connect_timeout field as a string instead of a TimeValue instance.
The reason that this is needed is because that the initial_connect_timeout field in the remote connection api is serialized for human consumption, but not for parsing purposes.
Therefore the HLRC can't parse it correctly (which caused test failures in CI, but not in the PR CI
:( ). The way this field is serialized needs to be changed in the remote connection api, but that is a breaking change. We should wait making this change until rest api versioning is introduced.
Co-Authored-By: j-bean <anton.shuvaev91@gmail.com>
Co-authored-by: j-bean <anton.shuvaev91@gmail.com>
* Add ILM histore store index (#50287)
* Add ILM histore store index
This commit adds an ILM history store that tracks the lifecycle
execution state as an index progresses through its ILM policy. ILM
history documents store output similar to what the ILM explain API
returns.
An example document with ALL fields (not all documents will have all
fields) would look like:
```json
{
"@timestamp": 1203012389,
"policy": "my-ilm-policy",
"index": "index-2019.1.1-000023",
"index_age":123120,
"success": true,
"state": {
"phase": "warm",
"action": "allocate",
"step": "ERROR",
"failed_step": "update-settings",
"is_auto-retryable_error": true,
"creation_date": 12389012039,
"phase_time": 12908389120,
"action_time": 1283901209,
"step_time": 123904107140,
"phase_definition": "{\"policy\":\"ilm-history-ilm-policy\",\"phase_definition\":{\"min_age\":\"0ms\",\"actions\":{\"rollover\":{\"max_size\":\"50gb\",\"max_age\":\"30d\"}}},\"version\":1,\"modified_date_in_millis\":1576517253463}",
"step_info": "{... etc step info here as json ...}"
},
"error_details": "java.lang.RuntimeException: etc\n\tcaused by:etc etc etc full stacktrace"
}
```
These documents go into the `ilm-history-1-00000N` index to provide an
audit trail of the operations ILM has performed.
This history storage is enabled by default but can be disabled by setting
`index.lifecycle.history_index_enabled` to `false.`
Resolves#49180
* Make ILMHistoryStore.putAsync truly async (#50403)
This moves the `putAsync` method in `ILMHistoryStore` never to block.
Previously due to the way that the `BulkProcessor` works, it was possible
for `BulkProcessor#add` to block executing a bulk request. This was bad
as we may be adding things to the history store in cluster state update
threads.
This also moves the index creation to be done prior to the bulk request
execution, rather than being checked every time an operation was added
to the queue. This lessens the chance of the index being created, then
deleted (by some external force), and then recreated via a bulk indexing
request.
Resolves#50353
* Update remote cluster stats to support simple mode (#49961)
Remote cluster stats API currently only returns useful information if
the strategy in use is the SNIFF mode. This PR modifies the API to
provide relevant information if the user is in the SIMPLE mode. This
information is the configured addresses, max socket connections, and
open socket connections.
* Send hostname in SNI header in simple remote mode (#50247)
Currently an intermediate proxy must route conncctions to the
appropriate remote cluster when using simple mode. This commit offers
a additional mechanism for the proxy to route the connections by
including the hostname in the TLS SNI header.
* Rename the remote connection mode simple to proxy (#50291)
This commit renames the simple connection mode to the proxy connection
mode for remote cluster connections. In order to do this, the mode specific
settings which we namespaced by their mode (ex: sniff.seed and
proxy.addresses) have been reverted.
* Modify proxy mode to support a single address (#50391)
Currently, the remote proxy connection mode uses a list setting for the
proxy address. This commit modifies this so that the setting is
proxy_address and only supports a single remote proxy address.
The "code_user" and "code_admin" reserved roles existed to support
code search which is no longer included in Kibana.
The "kibana_system" role included privileges to read/write from the
code search indices, but no longer needs that access.
Backport of: #50068
This adds a new `randomize_seed` for regression and classification.
When not explicitly set, the seed is randomly generated. One can
reuse the seed in a similar job in order to ensure the same docs
are picked for training.
Backport of #49990
Adds `GET /_script_language` to support Kibana dynamic scripting
language selection.
Response contains whether `inline` and/or `stored` scripts are
enabled as determined by the `script.allowed_types` settings.
For each scripting language registered, such as `painless`,
`expression`, `mustache` or custom, available contexts for the language
are included as determined by the `script.allowed_contexts` setting.
Response format:
```
{
"types_allowed": [
"inline",
"stored"
],
"language_contexts": [
{
"language": "expression",
"contexts": [
"aggregation_selector",
"aggs"
...
]
},
{
"language": "painless",
"contexts": [
"aggregation_selector",
"aggs",
"aggs_combine",
...
]
}
...
]
}
```
Fixes: #49463
**Backport**
Reindex sort never gave a guarantee about the order of documents being
indexed into the destination, though it could give a sense of locality
of source data.
It prevents us from doing resilient reindex and other optimizations and
it has therefore been deprecated.
Related to #47567
Reindex sort never gave a guarantee about the order of documents being
indexed into the destination, though it could give a sense of locality
of source data.
It prevents us from doing resilient reindex and other optimizations and
it has therefore been deprecated.
Related to #47567
This adds a `_source` setting under the `source` setting of a data
frame analytics config. The new `_source` is reusing the structure
of a `FetchSourceContext` like `analyzed_fields` does. Specifying
includes and excludes for source allows selecting which fields
will get reindexed and will be available in the destination index.
Closes#49531
Backport of #49690
This change adds a dynamic cluster setting named `indices.id_field_data.enabled`.
When set to `false` any attempt to load the fielddata for the `_id` field will fail
with an exception. The default value in this change is set to `false` in order to prevent
fielddata usage on this field for future versions but it will be set to `true` when backporting
to 7x. When the setting is set to true (manually or by default in 7x) the loading will also issue
a deprecation warning since we want to disallow fielddata entirely when https://github.com/elastic/elasticsearch/issues/26472
is implemented.
Closes#43599
This commit back ports three commits related to enabling the simple
connection strategy.
Allow simple connection strategy to be configured (#49066)
Currently the simple connection strategy only exists in the code. It
cannot be configured. This commit moves in the direction of allowing it
to be configured. It introduces settings for the addresses and socket
count. Additionally it introduces new settings for the sniff strategy
so that the more generic number of connections and seed node settings
can be deprecated.
The simple settings are not yet registered as the registration is
dependent on follow-up work to validate the settings.
Ensure at least 1 seed configured in remote test (#49389)
This fixes#49384. Currently when we select a random subset of seed
nodes from a list, it is possible for 0 seeds to be selected. This test
depends on at least 1 seed being selected.
Add the simple strategy to cluster settings (#49414)
This is related to #49067. This commit adds the simple connection
strategy settings and strategy mode setting to the cluster settings
registry. With these changes, the simple connection mode can be used.
Additionally, it adds validation to ensure that settings cannot be
misconfigured.
This commit replaces the _estimate_memory_usage API with
a new API, the _explain API.
The API consolidates information that is useful before
creating a data frame analytics job.
It includes:
- memory estimation
- field selection explanation
Memory estimation is moved here from what was previously
calculated in the _estimate_memory_usage API.
Field selection is a new feature that explains to the user
whether each available field was selected to be included or
not in the analysis. In the case it was not included, it also
explains the reason why.
Backport of #49455
This commit adds a deprecation warning when starting
a node where either of the server contexts
(xpack.security.transport.ssl and xpack.security.http.ssl)
meet either of these conditions:
1. The server lacks a certificate/key pair (i.e. neither
ssl.keystore.path not ssl.certificate are configured)
2. The server has some ssl configuration, but ssl.enabled is not
specified. This new validation does not care whether ssl.enabled is
true or false (though other validation might), it simply makes it
an error to configure server SSL without being explicit about
whether to enable that configuration.
Backport of: #45892
* [ML] ML Model Inference Ingest Processor (#49052)
* [ML][Inference] adds lazy model loader and inference (#47410)
This adds a couple of things:
- A model loader service that is accessible via transport calls. This service will load in models and cache them. They will stay loaded until a processor no longer references them
- A Model class and its first sub-class LocalModel. Used to cache model information and run inference.
- Transport action and handler for requests to infer against a local model
Related Feature PRs:
* [ML][Inference] Adjust inference configuration option API (#47812)
* [ML][Inference] adds logistic_regression output aggregator (#48075)
* [ML][Inference] Adding read/del trained models (#47882)
* [ML][Inference] Adding inference ingest processor (#47859)
* [ML][Inference] fixing classification inference for ensemble (#48463)
* [ML][Inference] Adding model memory estimations (#48323)
* [ML][Inference] adding more options to inference processor (#48545)
* [ML][Inference] handle string values better in feature extraction (#48584)
* [ML][Inference] Adding _stats endpoint for inference (#48492)
* [ML][Inference] add inference processors and trained models to usage (#47869)
* [ML][Inference] add new flag for optionally including model definition (#48718)
* [ML][Inference] adding license checks (#49056)
* [ML][Inference] Adding memory and compute estimates to inference (#48955)
* fixing version of indexed docs for model inference
Backport of #48849. Update `.editorconfig` to make the Java settings the
default for all files, and then apply a 2-space indent to all `*.gradle`
files. Then reformat all the files.
* [ML] Add new geo_results.(actual_point|typical_point) fields for `lat_long` results (#47050)
[ML] Add new geo_results.(actual_point|typical_point) fields for `lat_long` results (#47050)
Related PR: https://github.com/elastic/ml-cpp/pull/809
* adjusting bwc version
This commit finishes cleaning up the AbstractHlrcXContentTestCase work
and removes this class. All classes that were using this are now using
the updated base class.
Ref #39745
The old graph tests were duplicated a lot and used a deprecated parent
class. This commit cleans that up and removes one of the duplicated
tests.
Ref #39745
* [ML][Inference] separating definition and config object storage (#48651)
This separates out the `definition` object from being stored within the configuration object in the index.
This allows us to gather the config object without decompressing a potentially large definition.
Additionally, `input` is moved to the TrainedModelConfig object and out of the definition. This is so the trained input fields are accessible outside the potentially large model definition.
Adding support for the `search_type` request parameter to the Ranking Evaluation
API since this parameter can impact the ranking and the metric score and should
be choosen in the same way when evaluating the search as later in the real
search.
Closes#48503
Backport of #48447. Make a number of changes so that code in the
`client` directory is more resilient to automatic formatting. This
covers:
* Literal JSON handling:
* Reformatting multiline JSON to embed whitespace in the strings
* Remove string concatenation where JSON fits on a single line
* Use `String.format` for large documents with variable content
* Remove some erroneous doc refs in `QueryDSLDocumentationTests`
* Move some comments around to they aren't auto-formatted to a strange
place
This commit simplifies and standardizes our usage of the Gradle Shadow
plugin to conform more to plugin conventions. The custom "bundle" plugin
has been removed as it's not necessary and performs the same function
as the Shadow plugin's default behavior with existing configurations.
Additionally, this removes unnecessary creation of a "nodeps" artifact,
which is unnecessary because by default project dependencies will in
fact use the non-shadowed JAR unless explicitly depending on the
"shadow" configuration.
Finally, we've cleaned up the logic used for unit testing, so we are
now correctly testing against the shadow JAR when the plugin is applied.
This better represents a real-world scenario for consumers and provides
better test coverage for incorrectly declared dependencies.
(cherry picked from commit 3698131109c7e78bdd3a3340707e1c7b4740d310)
Due to a bug, GETing a snapshot can cause a RespositoryException to be
thrown. This error is transient and should be retried, rather than
causing the test to fail. This commit converts those
RepositoryExceptions into AssertionErrors so that they will be retried
in code wrapped in assertBusy.
BytesReference is currently an abstract class which is extended by
various implementations. This makes it very difficult to use the
delegation pattern. The implication of this is that our releasable
BytesReference is a PagedBytesReference type and cannot be used as a
generic releasable bytes reference that delegates to any reference type.
This commit makes BytesReference an interface and introduces an
AbstractBytesReference for common functionality.
The AbstractHlrcWriteableXContentTestCase was replaced by a better test
case a while ago, and this is the last two instances using it. They have
been converted and the test is now deleted.
Ref #39745
This commit removes the randomization used by every execute call in the
high level rest tests. Previously every execute call, which can be many
calls per single test, would rely on a random boolean to determine if
they should use the sync or async methods provided to the execute
method. This commit runs the tests twice, using two different clusters,
both of them providing the value one time via a sysprop. This ensures
that the whole suite of tests is run using the sync and async code
paths.
Closes#39667
All internal searches (triggered by APIs) across the .security index
must be performed while "under the security origin". Otherwise,
the search is performed in the context of the caller which most
likely does not have privileges to search .security (hopefully).
This commit fixes this in the case of two methods in the
TokenService and corrects an overly done such context switch
in the ApiKeyService.
In addition, this makes all tests from the client/rest-high-level
module execute as an all mighty administrator,
but not a literal superuser.
Closes#47151
Several links from the ILM HLRC Javadoc to the online documentation were
not updated when the ILM HLRC documentation was written. This commit
fixes those links.
Adds `GET /_script_context`, returning a `contexts` object with each
available context as a key whose value is an empty object. eg.
```
{
"contexts": {
"aggregation_selector": {},
"aggs": {},
"aggs_combine": {},
...
}
}
```
refs: #47411
This adds parsing an inference model as a possible
result of the analytics process. When we do parse such a model
we persist a `TrainedModelConfig` into the inference index
that contains additional metadata derived from the running job.
which is backport merge and adds a new ingest processor, named enrich processor,
that allows document being ingested to be enriched with data from other indices.
Besides a new enrich processor, this PR adds several APIs to manage an enrich policy.
An enrich policy is in charge of making the data from other indices available to the enrich processor in an efficient manner.
Related to #32789
This change adds:
- A new option, allow_lazy_open, to anomaly detection jobs
- A new option, allow_lazy_start, to data frame analytics jobs
Both work in the same way: they allow a job to be
opened/started even if no ML node exists that can
accommodate the job immediately. In this situation
the job waits in the opening/starting state until ML
node capacity is available. (The starting state for data
frame analytics jobs is new in this change.)
Additionally, the ML nightly maintenance tasks now
creates audit warnings for ML jobs that are unassigned.
This means that jobs that cannot be assigned to an ML
node for a very long time will show a yellow warning
triangle in the UI.
A final change is that it is now possible to close a job
that is not assigned to a node without using force.
This is because previously jobs that were open but
not assigned to a node were an aberration, whereas
after this change they'll be relatively common.
This commit adds HLRC support and documentation for the SLM Start and
Stop APIs, as well as updating existing documentation where appropriate.
This commit also ensures that the SLM APIs are properly included in the
HLRC documentation.
Elastic cloud has a concept of a cloud Id. This Id is a base64 encoded
url, split up into a few parts. This commit allows the user to pass in a
cloud id now, which is translated to a HttpHost that is defined by the
encoded parts therein.
Adds a new datafeed config option, max_empty_searches,
that tells a datafeed that has never found any data to stop
itself and close its associated job after a certain number
of real-time searches have returned no data.
Backport of #47922
This commit adds two APIs that allow to pause and resume
CCR auto-follower patterns:
// pause auto-follower
POST /_ccr/auto_follow/my_pattern/pause
// resume auto-follower
POST /_ccr/auto_follow/my_pattern/resume
The ability to pause and resume auto-follow patterns can be
useful in some situations, including the rolling upgrades of
cluster using a bi-directional cross-cluster replication scheme
(see #46665).
This commit adds a new active flag to the AutoFollowPattern
and adapts the AutoCoordinator and AutoFollower classes so
that it stops to fetch remote's cluster state when all auto-follow
patterns associate to the remote cluster are paused.
When an auto-follower is paused, remote indices that match the
pattern are just ignored: they are not added to the pattern's
followed indices uids list that is maintained in the local cluster
state. This way, when the auto-follow pattern is resumed the
indices created in the remote cluster in the meantime will be
picked up again and added as new following indices. Indices
created and then deleted in the remote cluster will be ignored
as they won't be seen at all by the auto-follower pattern at
resume time.
Backport of #47510 for 7.x
Benjamin Trent
Nhat Nguyen
Martijn van Groningen
Tim Vernum
Dimitris Athanasiou
Darren Foong
Julie Tibshirani
Nik Everett
Adrien Grand
Lee Hinman
Przemysław Witek
Tim Brooks
James Baiera
Stuart Tettemer
Henning Andersen
Henning Andersen
Jim Ferenczi
jesinity
Rory Hunter
Alan Woodward
Michael Basnight
Dan Hermann
Gordon Brown
Christoph Büscher
Mark Vieira
David Turner
Tanguy Leroux
Albert Zaharovits
David Roberts
Yogesh Gaikwad
Hendrik Muhs